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3 days ago
Requirements and responsibilities
Job Summary: In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.Key Responsibilities:Design, implement, and maintain scalable infrastructure solutions using Kubernetes across AWS and GCP environments.Develop, manage, and optimize CI/CD pipelines to ensure seamless integration and continuous delivery for diverse applications.Automate infrastructure management, monitoring, and deployments with Python and DevOps best practices.Collaborate closely with cross-functional teams to support robust cloud-native architectures and application reliability.Monitor system performance, troubleshoot issues, and implement proactive solutions for optimization and security.Document processes, architectures, and solutions clearly for technical and non-technical audiences.Champion a culture of transparent communication and knowledge sharing within the customer's team.Required Skills and Qualifications:Expertise in Kubernetes orchestration and management of containerized applications.Hands-on experience with both AWS and GCP cloud platforms.Proven ability to develop automation scripts and tools using Python.Deep understanding of infrastructure-as-code, CI/CD pipelines, and DevOps principles.Excellent written and verbal communication skills and a collaborative mindset.Experience with monitoring, logging, and proactive system management.Strong problem-solving abilities in complex, distributed cloud environments.Preferred Qualifications:Certifications related to Kubernetes, AWS, or GCP.Prior work in AI/ML infrastructure or data-intensive environments.Familiarity with additional programming languages or automation frameworks.Required Skills: Kubernetes, AWS, GCP, Python
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